Nowadays, deep neural networks are widely used in mission critical systems such as
healthcare, self-driving vehicles, and military which have direct impact on human lives …

In the last few years, Artificial Intelligence (AI) has achieved a notable momentum that, if
harnessed appropriately, may deliver the best of expectations over many application sectors …

At the dawn of the fourth industrial revolution, we are witnessing a fast and widespread
adoption of artificial intelligence (AI) in our daily life, which contributes to accelerating the …

Given the recent surge in developments of deep learning, this paper provides a review of the
state-of-the-art deep learning techniques for audio signal processing. Speech, music, and …

A substantial amount of research has been carried out in Explainable Artificial Intelligence
(XAI) models, especially in those which explain the deep architectures of neural networks. A …

With the advent of advancements in deep learning approaches, such as deep convolution
neural network, residual neural network, adversarial network; U-Net architectures are most …

In recent years, machine learning-based intrusion detection systems (IDSs) have proven to
be effective; especially, deep neural networks improve the detection rates of intrusion …

The Internet revolution and Moore's Law drove the rapid expansion of connected consumer
electronics. As massive data is generated by Internet of Things (IoT) devices, edge …

Time series data is increasingly used in a wide range of fields, and it is often relied on in
crucial applications and high-stakes decision-making. For instance, sensors generate time …

Prostate cancer is one of the most common forms of cancer in men in many countries. The
survival rate can be significantly enhanced with early detection of the cancer so that …